SAR图像CFAR检测的快速算法综述

针对合成孔径雷达(Synthetic aperture radar, SAR)图像目标检测中恒虚警率(Constant false alarm rate, CFAR)算法的广泛应用, 进行CFAR检测的快速算法分析具有重要研究价值. 首先概述了当前国内外对SAR图像CFAR检测快速算法的研究现状; 然后分别从快速预筛选和迭代计算方法两个方面对各类快速算法的实时性及性能进行了分析总结, 给出了四种基本CFAR检测器的迭代计算公式, 并提出了一种研究CFAR检测快速算法的基本框架, 现有的快速算法均可纳入该理论框架予以分析; 最后, 以经典双参数CFAR检测算法为例, 对该基本框架进行仿真实现和性能分析, 验证了其可行性与检测性能．结果表明: 新的CFAR检测快速算法基本框架充分融合了快速预筛选思想和迭代计算方法的优势, 有效提高了CFAR算法在SAR图像检测应用中的执行效率.

Survey on Fast CFAR Detection Algorithms for SAR Image Targets

Due to extensive applications of constant false alarm rate (CFAR) algorithms to the synthetic aperture radar (SAR) image target detection, an analysis on fast CFAR detection algorithms is significant. This paper begins with a survey of fast CFAR detection algorithms. An intensive analysis on their performance and computational complexity is performed with the most two important steps, i.e., rapid pre-screening and iterative computation. The iterative computational formulae of four common CFAR detectors are then presented. A novel framework on fast CFAR detection algorithm analysis is proposed, which can be employed to analyze all of the current fast algorithms. Finally, based on the classic two-parameter CFAR algorithm, the framework is simulated and analyzed, and its feasibility and performance are validated. The results show that the new framework sufficiently integrates the advantages of rapid pre-screening and iterative computation, and effectively improves execution efficiency of the CFAR algorithm in SAR images detection.